Last Updated: 12/2025
Start Date Jan 01, 2026
Duration 120 Days
EMI Starting At ₹10000
Language Availability Both English & Hindi

Course Key Highlights:

Hours of Instructor-Led Training
Flexible Schedule
22 Hours of Self-Paced Videos
Certification
Job Assistance
Lifetime Free Upgrade
56 Hours of Projects Exercises
Hours of Instructor-Led Training
Why should you opt for this course?
  • Comprehensive and Structured Skill Development

What will you learn?

  • Fundamental and Advanced Programming Skills (Python).

Who should enroll?

Students in Classes 8 to 10
Students in Classes 8 to 10

Students who wish to build strong technical skills should enroll,

Beginners and Students Seeking Structured Learning
Beginners and Students Seeking Structured Learning

Students who wish to build strong technical skills should enroll,

Students Aiming for Strong Python, Data Handling, and AI Ethics Skills
Students Aiming for Strong Python, Data Handling, and AI Ethics Skills

Students Aiming for Strong Python, Data Handling, and AI Ethics Skills

What are the prerequisites?

What is the price?

₹12000 ₹10000
₹10000 Buy Now

Course Curriculum

MODULE 1 — FOUNDATIONS OF COMPUTERS, AI & CODING (Weeks 1–2) 6 lectures

WEEK 1 — Introduction to Computers & AI

Learning Outcomes

  • Understand basics of computers and AI
  • Identify real-life AI applications
  • Difference between AI, ML, DL

Topics

  1. What is a Computer?
  2. What is Artificial Intelligence?
  3. Real-world applications of AI
  4. Difference → AI vs ML vs DL
  5. Responsible & Ethical AI

Hands-on Labs

  1. Activity: “AI Around Us” worksheet
  2. Activity: Classifying AI vs Non-AI applications
  3. Small poster: “Future of AI in My Life”

WEEK 2 — Basics of Coding & Algorithms

Learning Outcomes

Understand the logic of coding

Build simple algorithms

Use flowcharts to solve problems

Topics

What is Coding?

Algorithms — step-by-step logic

Flowcharts

Types of programming languages

Introduction to Python environment (online/offline)

Hands-on Labs

Draw a flowchart for “Making Tea / Ordering Food Online”

Create first Python program: print("Hello AI World")

MODULE 2 — PYTHON PROGRAMMING (Weeks 3–6) 15 lectures

WEEK 3 — Python Basics

Learning Outcomes

  • Use variables, data types, and operators
  • Take user input and display output

Topics

  1. Variables & Data Types
  2. Input & Output
  3. Operators (Arithmetic, Comparison)
  4. Simple expressions

Hands-on Labs

  • Build a Calculator
  • Create a Temperature Converter
  • Write 10 simple mathematical programs

WEEK 4 — Decision Making in Python

Learning Outcomes

  • Apply logic using conditional statements
  • Build simple rule-based programs

Topics

  1. If Statement
  2. If–Else
  3. Nested Conditions
  4. Logical Operators (AND/OR/NOT)

Hands-on Labs

  1. Age Classifier
  2. Grading System Program
  3. ATM Mini-System (withdrawal allowed/not allowed)

WEEK 5 — Loops & Patterns

Learning Outcomes

  • Use loops to repeat actions
  • Understand patterns and sequences

Topics

  1. For Loop
  2. While Loop
  3. Loop Control → break, continue
  4. Number & Star Patterns

Hands-on Labs

  • Number Guessing Game
  • Multiplication Table Generator
  • Star Pattern Creator

WEEK 6 — Data Structures

Learning Outcomes

  • Store and process data in lists/dictionaries
  • Apply loops with data structures

Topics

  1. Lists
  2. List Methods
  3. Dictionaries
  4. Dictionary operations
  5. Intro to Tuples

Hands-on Labs

  • Contact Book Program
  • Shopping Cart Simulator
  • Student Marks Summary System
MODULE 3 — INTRODUCTION TO AI & MACHINE LEARNING (Weeks 7–9) 15 lectures

WEEK 7 — Understanding Data & AI

Learning Outcomes

  • Understand how data powers AI
  • Identify features, labels
  • Analyze good vs bad data

Topics

  1. What is Data?
  2. Types of Data — Images, Numbers, Text
  3. Features & Labels (simple concept)
  4. Data Collection + Dataset creation

Hands-on Labs

  1. Create a dataset of classroom objects (mobile pics)
  2. Label data in a simple table
  3. Activity: Spot biased datasets

WEEK 8 — Machine Learning Concepts (Beginner Level)

Learning Outcomes

  • Understand ML workflow
  • Difference between training/testing
  • Learn supervised vs unsupervised ML

Topics

  1. What is ML?
  2. ML Workflow
  3. Supervised vs Unsupervised Learning
  4. Classification vs Regression (concept only)

Hands-on Labs

  1. Fruit Classifier using shapes & colors
  2. Create a simple decision tree on paper
  3. ML Game: Predict exam results from sample data

WEEK 9 — No-Code AI Model Building

Learning Outcomes

  • Train and test AI models using simple tools
  • Build real projects using images, sound, pose detection

Tools: Teachable Machine / PictoBlox / Scratch AI

Topics

  1. Image Classification
  2. Pose Classification
  3. Sound Classification

Hands-on Labs

  1. Train an Image Model: Identify classroom items
  2. Sound Detection Model: Clap → Action
  3. Pose Model for “Rock-Paper-Scissors”
MODULE 4 — PYTHON FOR AI & REAL PROJECTS (Weeks 10–12) 15 lectures
  1. WEEK 10 — Python for AI

Learning Outcomes

  • Simulate AI logic using Python
  • Work with lists & dictionaries for decision-making

Topics

  1. Importing libraries
  2. Random module
  3. Dictionary-based AI
  4. Rule-Based Chatbots

Hands-on Labs

  • Build a Simple Chatbot
  • Create a Dice Simulator
  • Build a Quiz Generator

WEEK 11 — Introduction to Neural Networks (Age-Friendly Concept)

Learning Outcomes

  • Understand neurons and layers
  • See how AI makes predictions

Topics

  1. What is a Neuron?
  2. Layers (Input–Hidden–Output)
  3. How predictions work
  4. Human Neural Network Roleplay

Hands-on Labs

  • Build a Paper Neural Network
  • Group Activity: Students act as neurons passing signals
  • Predict outcomes using a simple "weight table"

WEEK 12 — Major AI Projects

Learning Outcomes

  • Build end-to-end AI projects
  • Present AI solutions
  • Work individually or in teams

Project Options

  1. Image Classifier for Animals/Objects
  2. AI Quiz Bot
  3. Weather Advisory Chatbot
  4. Attendance Predictor (sample dataset)
  5. Safety Alerts System (rule-based AI)

Hands-on Labs

Project Building

Testing & Refinement

Presentation Day

Course Projects

PROJECT 1: Image Classification Model (Using Teachable Machine)

Project Description Students train a simple AI model to recognize different objects (fruits, school items, shapes) using images. Learning Outcomes Understanding datasets (images) Training vs Testing How AI makes predictions Tools Needed Laptop with camera Teachable Machine (web-based)

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PROJECT 2: Python Chatbot (Rule-Based AI)

Project Description Students build a chatbot that answers basic questions—for example: School timing Subjects info Bus schedule Simple greetings Learning Outcomes If–else logic Decision-making Simulating AI behavior

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PROJECT 3: AI Quiz Generator (Python + Random Module)

Project Description Students build a quiz that asks math/science questions randomly and gives scores. Learning Outcomes Lists & dictionaries Random module Looping through questions

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PROJECT 4: Smart Safety Alert System (Rule-Based AI Simulation)

Project Description Students simulate an AI system that gives alerts based on conditions like: Temperature too high Water level too low Motion detected Learning Outcomes Understanding rule-based AI Using conditions + sensors simulation Problem-solving

Read More

Tools Covered

Python

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Frequently Asked Question

This course introduces students to Artificial Intelligence, Python programming, problem-solving, and real-world AI applications using hands-on projects and no-code tools.

Students from Class 8, 9, and 10 with basic computer knowledge.
No prior programming experience is required.

Students will learn:

  • Python Programming Basics
  • Logic Building & Algorithms
  • AI Concepts (ML, Data, Neural Networks)
  • Image, Sound & Text AI Models (no-code)
  • Real-world Projects & Problem-Solving

Yes, a laptop or desktop with internet access is recommended for coding and AI model training.

Not at all.
We use a step-by-step, beginner-friendly approach with simple examples and guided practice.

No.
The course starts from zero level and gradually moves to intermediate topics.

Students will learn Python, the most popular and easiest language for AI and programming.

We use:

  • Python (Thonny/VS Code)
  • Teachable Machine
  • PictoBlox / Scratch AI
  • Online IDEs
    These tools are safe and easy for students to use.

Students create fun and real AI projects such as:

  • Image Recognition Model
  • AI Chatbot
  • Quiz Generator
  • Smart Safety Alert System
  • Pose / Sound Detection Models

Yes. A certificate is awarded after completing all modules and the final project.

Career Scope?

    • Python Programming Expertise:

Frequently bought together

FULL STACK WEB DEVELOPMENT


10-20 hours
Live Project

Your Instructors

Person

Abhinav Thakur

Senior Full Stack Developer with 10+ years of extensive experience in designing, developing, and deploying scalable web applications across modern tech stacks. Skilled in leading projects, mentoring teams, and delivering high-quality solutions.